---
license: apache-2.0
base_model: projecte-aina/roberta-base-ca-v2-cased-te
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 2504v4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 2504v4

This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cased-te](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cased-te) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6121
- Accuracy: 0.8193
- Precision: 0.8296
- Recall: 0.8193
- F1: 0.8179
- Ratio: 0.5882

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 4
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Ratio  |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 2.127         | 0.9870 | 38   | 0.8502          | 0.6345   | 0.6397    | 0.6345 | 0.6310 | 0.5966 |
| 0.7538        | 2.0    | 77   | 0.6640          | 0.7689   | 0.7885    | 0.7689 | 0.7649 | 0.6303 |
| 0.6205        | 2.9870 | 115  | 0.6121          | 0.8193   | 0.8296    | 0.8193 | 0.8179 | 0.5882 |
| 0.5664        | 3.9481 | 152  | 0.6239          | 0.8109   | 0.8278    | 0.8109 | 0.8085 | 0.6134 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1